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There is a fourth question, not considered here, related to the length of the branch.
This question is valid in the context of Phylogenetic Diversity [ PD ] (Faith 1992 ),
Genetic Diversity [GD] (Crozier 1992 ), or total lineage divergence (Scheiner 2012 )
[a metric similar to PD]. These methods require the precise estimation of the length,
therefore the accuracy of the index value depends heavily on the length estimation.
Although Krajewski ( 1994 ) considers that the debate of the use and calculations
of divergence in systematics and conservation are two topics, I consider that the
same criticisms to the accuracy estimation of the length in systematics will have a
profound impact in the decision made when the topology and its branch length s are
used in conservation. And as this quotation from Brown et al. ( 2010 ) states, “in any
phylogenetic analysis, the biological plausibility of branch-length output must be
carefully considered”. Therefore, we must be well aware of the methodological
approach used to construct the phylogeny (Rannala et al. 2012 ).
Additionally, in some cases we must consider the sensitivity of PD value to intra-
specifi c variation (Albert et al. 2012 ). Therefore, we must take into account the
source of the tree (species vs. gene trees) [see for example Spinks and Shaffer
( 2009 )].
Optimal Scenario
Given a data set and n random perturbations on this data, if the index is robust, all
(or most) perturbations would yield the same general ranking. Therefore, in the
context of conservation in an optimal situation, we would prefer areas that:
Have the same position in the ranking ( original and re - sampled ), no matter if we
delete areas , species , or phylogenies
= same ranking or position , insensitive to changes in the item ( s ) deleted.
if not, at least must be the same position in the ranking but considering just a
subgroup (e.g. be fi rst or second, or fi rst to third).
Have the same position in the ranking ( original and re - sampled ), no matter the-
delete probability used ( from 0.01 to 0.5 ).
= same ranking or position , insensitive to changes in the delete probability.
or, have the same position for most of the probabilities used, but not counting
extreme situations as a delete probability of 0.5.
= not too sensitive to the probability values used.
In a real world, an scenario to meet the requirements of the fi rst and third condi-
tions is too strict and maybe impossible to fulfi ll. Therefore, my decision rules to
select the best index and the best ranking are based in the second and fourth situa-
tions. The area must have the same position in the ranking considering just a sub-
group, from the fi rst to the third position in the ranking, no matter the type of item
deleted, and for most of the probability values.
An alternative measure is to evaluate the behavior of an index and its success as
the number of times that a replicate recovers part of the original ranking (e.g.
D.R. Miranda-Esquivel